[R-sig-ME] need help with mixed effects model

[Mark W Kimpel]

This is my first foray into in mixed models and, while awaiting the 
arrival of:

Extending the Linear Model with R: Generalized Linear, Mixed Effects 
and 	Nonparametric Regression Models
Mixed Effects Models in S and S-Plus

I am in need to some advice.

I would like to look at gene-gene correlations within a multi-factorial,
mixed effects experiment. Here are the factors, with levels:

Gene Expression: 2 different genes per Animal, continuous variable
Animals: 6 per Strain
Tissues: 3 per animal
Strain: 2

I thus have 6*3*2 = 36 samples

I do not care, for this analysis, about differences between Tissues, 
Strains, or Animals, in fact, I want to control for them while examining 
the correlation of expression of the two genes. In other words, I want 
look at something very much like the Pearson correlation coefficient 
controlled for these other factors.

I guess the first question I should ask is: "is a mixed model the way to 
go, and, if not, what would be the correct approach?"

Assuming mixed models will work, as I see it through my newbie eyes, 
Tissue and strain are fixed effects and animals are random effects.

Any suggestions for an approach and a model?

Mark

Mark W. Kimpel MD  ** Neuroinformatics ** Dept. of Psychiatry
Indiana University School of Medicine

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